If we build it they will come: targeting the immune response to breast cancer
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Full frame distilled prediction
Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
- Candidate categories
- Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
- Consensus categories
- none
- Domain
- Candidate signal: noneConsensus signal: none
- Study design
- Candidate signal: Not applicableConsensus signal: none
- Genre
- Candidate signal: ReviewConsensus signal: Review
- Teacher disagreement score
- 0.950
- Threshold uncertainty score
- 1.000
- Validation status
machine_predicted_unvalidated·codex-gemma-dda1882f352a
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
- Teacher spread
- 0.313 · how far apart the two teachers sit on this one work
- Validation status
score_only:v0-immature-baseline· verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it
Abstract
Historically, breast cancer tumors have been considered immunologically quiescent, with the majority of tumors demonstrating low lymphocyte infiltration, low mutational burden, and modest objective response rates to anti-PD-1/PD-L1 monotherapy. Tumor and immunologic profiling has shed light on potential mechanisms of immune evasion in breast cancer, as well as unique aspects of the tumor microenvironment (TME). These include elements associated with antigen processing and presentation as well as immunosuppressive elements, which may be targeted therapeutically. Examples of such therapeutic strategies include efforts to (1) expand effector T-cells, natural killer (NK) cells and immunostimulatory dendritic cells (DCs), (2) improve antigen presentation, and (3) decrease inhibitory cytokines, tumor-associated M2 macrophages, regulatory T- and B-cells and myeloid derived suppressor cells (MDSCs). The goal of these approaches is to alter the TME, thereby making breast tumors more responsive to immunotherapy. In this review, we summarize key developments in our understanding of antitumor immunity in breast cancer, as well as emerging therapeutic modalities that may leverage that understanding to overcome immunologic resistance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
The record
- Venue
- npj Breast Cancer
- Topic
- Cancer Immunotherapy and Biomarkers
- Field
- Medicine
- Canadian institutions
- Princess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
- Funders
- National Cancer Institute
- Keywords
- Tumor microenvironmentImmune systemImmunotherapyImmunologyAntigen presentationBreast cancerCancer researchMedicineAntigenCancer immunotherapyCancerBiologyT cellInternal medicine
- Has abstract in OpenAlex
- yes